Time trends in first admissions for schizophrenia and paranoid psychosis in Stockholm County, Sweden

Schizophr Res. 2001 Mar 1;47(2-3):247-54. doi: 10.1016/s0920-9964(00)00124-9.


Several studies have reported decreasing time trends in first diagnosed schizophrenia patients. The aim of this study was to analyze time trends for first admissions with a diagnosis of schizophrenia or a diagnosis of either schizophrenia or paranoid psychosis during 1978-1994 in Stockholm County, Sweden, with a population of around 1.8million. Information about first psychiatric admission with the diagnosis schizophrenia or paranoid psychosis for residents of Stockholm County was obtained from the Swedish population-based psychiatric inpatient register. Age-adjusted average yearly changes in first hospitalization rates were estimated in a Poisson regression model. Time trends in first admission rates were calculated from 1978 to 1994, while admissions during 1971 to 1977 were observed only to eliminate later re-admissions. First admissions for schizophrenia declined by 1.9% annually for females and by 1.3% for males, while first admissions for schizophrenia and paranoid psychosis together were unchanged over the study period for both genders. Our results indicate that the incidence of schizophrenia and paranoid psychosis taken together was essentially the same over the studied time period in Stockholm County, and that the apparent decline in first admission rates for schizophrenia may be an effect of changes in clinical diagnosis over time.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Catchment Area, Health
  • Female
  • Hospitalization / statistics & numerical data
  • Humans
  • Incidence
  • Male
  • Middle Aged
  • Paranoid Disorders / rehabilitation*
  • Patient Admission / statistics & numerical data*
  • Population Surveillance
  • Psychotic Disorders / rehabilitation*
  • Registries*
  • Schizophrenia / epidemiology*
  • Schizophrenia / rehabilitation*
  • Sweden / epidemiology
  • Time Factors